Cholangiocarcinoma imaging: from diagnosis to response assessment

Cholangiocarcinoma (CCA), a highly aggressive primary liver cancer arising from the bile duct epithelium, represents a substantial proportion of hepatobiliary malignancies, posing formidable challenges in diagnosis and treatment. Notably, the global incidence of intrahepatic CCA has seen a rise, necessitating a critical examination of diagnostic and management strategies, especially due to presence of close imaging mimics such as hepatocellular carcinoma (HCC) and combined hepatocellular carcinoma-cholangiocarcinoma (cHCC-CCA). Hence, it is imperative to understand the role of various imaging modalities such as ultrasound, computed tomography (CT), and magnetic resonance imaging (MRI), elucidating their strengths, and limitations in diagnostic precision and staging accuracy. Beyond conventional approaches, there is emerging significance of functional imaging tools including positron emission tomography (PET)-CT and diffusion-weighted (DW)-MRI, providing pivotal insights into diagnosis, therapeutic assessment, and prognostic evaluation. This comprehensive review explores the risk factors, classification, clinical features, and role of imaging in the holistic spectrum of diagnosis, staging, management, and restaging for CCA, hence serving as a valuable resource for radiologists evaluating CCA.

Model-free dynamic contrast-enhanced MRI analysis: differentiation between active tumor and necrotic tissue in patients with glioblastoma

OBJECTIVE

Treatment response assessment in patients with high-grade gliomas (HGG) is heavily dependent on changes in lesion size on MRI. However, in conventional MRI, treatment-related changes can appear as enhancing tissue, with similar presentation to that of active tumor tissue. We propose a model-free data-driven method for differentiation between these tissues, based on dynamic contrast-enhanced (DCE) MRI.

MATERIALS AND METHODS

The study included a total of 66 scans of patients with glioblastoma. Of these, 48 were acquired from 1 MRI vendor and 18 scans were acquired from a different MRI vendor and used as test data. Of the 48, 24 scans had biopsy results. Analysis included semi-automatic arterial input function (AIF) extraction, direct DCE pharmacokinetic-like feature extraction, and unsupervised clustering of the two tissue types. Validation was performed via (a) comparison to biopsy result (b) correlation to literature-based DCE curves for each tissue type, and (c) comparison to clinical outcome.

RESULTS

Consistency between the model prediction and biopsy results was found in 20/24 cases. An average correlation of 82% for active tumor and 90% for treatment-related changes was found between the predicted component and population-based templates. An agreement between the predicted results and radiologist's assessment, based on RANO criteria, was found in 11/12 cases.

CONCLUSION

The proposed method could serve as a non-invasive method for differentiation between lesion tissue and treatment-related changes.

Incidence of Tumour Progression and Pseudoprogression in High-Grade Gliomas: a Systematic Review and Meta-Analysis

Background

High-grade gliomas are the most common primary brain tumours. Pseudoprogression describes the false appearance of radiation-induced progression on MRI. A distinction should be made from true tumour progression to correctly plan treatment. However, there is wide variation of reported pseudoprogression. We thus aimed to establish the incidence of pseudoprogression and tumour progression in high-grade glioma patients with a systematic review and meta-analysis.

Methods

We searched PubMed, Embase and Web of Science on the incidence of pseudoprogression and tumour progression in adult high-grade glioma patients from 2005, the latest on 8 October 2014. Histology or imaging follow-up was used as reference standard. Extracted data included number of patients with worsening of imaging findings on T1 postcontrast or T2/FLAIR, pseudoprogression and tumour progression. Study quality was assessed. Heterogeneity was tested with I². Pooling of the results was done with random models using Metaprop in STATA (StataCorp. Stata Statistical Software. College Station, TX: StataCorp LP).

Results

We identified 73 studies. MRI progression occurred in 2603 patients. Of these, 36% (95% confidence interval [CI] 33–40%) demonstrated pseudoprogression, 60% (95%CI 56–64%) tumour progression and unknown outcome was present in the remaining 4% of the patients (range 1–37%).

Conclusion

This meta-analysis demonstrated for the first time a notably high pooled incidence of pseudoprogression in patients with a form of progression across the available literature. This highlighted the full extent of the problem of the currently conventional MRI-based Response Assessment in Neuro-Oncology (RANO) criteria for treatment evaluation in high-grade gliomas. This underscores the need for more accurate treatment evaluation using advanced imaging to improve diagnostic accuracy and therapeutic approach.

Electronic supplementary material

The online version of this article (doi: 10.1007/s00062-017-0584-x) contains supplementary material, which is available to authorized users. It contains the characteristics of the included studies (supplementary table 1) and a full search strategy (see supplementary search strategy).

An artificial neural networks approach for assessment treatment response in oncological patients using PET/CT images

Background

Positron Emission Tomography – Computed Tomography (PET/CT) imaging is the basis for the evaluation of response-to-treatment of several oncological diseases. In practice, such evaluation is manually performed by specialists, which is rather complex and time-consuming. Evaluation measures have been proposed, but with questionable reliability. The usage of before and after-treatment image descriptors of the lesions for treatment response evaluation is still a territory to be explored.

Methods

In this project, Artificial Neural Network approaches were implemented to automatically assess treatment response of patients suffering from neuroendocrine tumors and Hodgkyn lymphoma, based on image features extracted from PET/CT.

Results

The results show that the considered set of features allows for the achievement of very high classification performances, especially when data is properly balanced.

Conclusions

After synthetic data generation and PCA-based dimensionality reduction to only two components, LVQNN assured classification accuracies of 100%, 100%, 96.3% and 100% regarding the 4 response-to-treatment classes.

Present and future roles of FDG-PET/CT imaging in the management of malignant pleural mesothelioma

Positron emission tomography/computed tomography (PET/CT) integrated with 2-[(18)F]fluoro-2-deoxy-D-glucose ((18)F-FDG) has emerged as a powerful tool for combined metabolic and anatomic evaluations in clinical oncologic imaging. This review discusses the utility of (18)F-FDG PET/CT as a tool to manage patients with malignant pleural mesothelioma. We discuss different stages of patient management in malignant pleural mesothelioma, including diagnosis, initial staging, therapy planning, early treatment response assessment, re-staging, and prognosis.

Present and future roles of FDG-PET/CT imaging in the management of lung cancer

Integrated positron emission tomography/computed tomography (PET/CT) using 2-[(18)F]fluoro-2-deoxy-D-glucose ((18)F-FDG) has emerged as a powerful tool for combined metabolic and anatomic evaluation in clinical oncologic imaging. This review discusses the utility of (18)F-FDG PET/CT as a tool for managing patients with lung cancer. We discuss different patient management stages, including diagnosis, initial staging, therapy planning, early treatment response assessment, re-staging, and prognosis.

¹⁸F-FDG-PET/CT in staging, restaging, and treatment response assessment of male breast cancer

PURPOSE

Male breast cancer (BC) is a rare disease, with patterns different from those found in women. Most tumors are detected at more advanced stages than in women. The aim of this study was to analyze the performance of [18F]fluorodeoxyglucose positron emission tomography/computed tomography ((18)F-FDG-PET/CT) in staging, restaging, and therapy response assessment.

METHODS

We performed a systematic analysis in the database of Saint-Louis Hospital to identify male patients with BC referred for PET/CT. (18)F-FDG-PET/CT findings considered suspicious for malignancy were compared to biopsy results, further work-up and/or patient follow-up of at least 6 months. Performances of (18)F-FDG-PET/CT were compared to that of conventional imaging (CI) using the McNemar test. The impact of PET/CT on management was evaluated.

RESULTS

During 6 consecutive years, among 12,692 (18)F-FDG-PET/CT oncology studies, 30 were performed in 15 men with BC: 7 examinations for initial staging, 11 for restaging, and 12 for response assessment. Tumors profile was ER+ and one had HER2 overexpression. PET/CT sensitivity, specificity, positive predictive value, negative predictive value and accuracy to detect distant metastases were 100%, 67%, 86%, 100% and 89%, respectively. PET/CT was more informative than CI in 40% of studies (p=0.03; 95% confidence interval: 3.26 - 40%). Findings from (18)F-FDG-PET/CT led to modification in the planned treatment in 13/30 cases (43%).

CONCLUSION

Although all the tumors were ER+, primary lesions and metastases were diagnosed with high sensitivity. (18)F-FDG-PET/CT seems to be a powerful imaging method to perform staging, restaging and treatment response assessment in male patients with BC.